1. Field
The present disclosure relates to a system and a method for detecting multi-level intrusion events.
2. Description of Related Art
Intrusion detection is currently the most focused intelligent visual recognition technique. Along with the advancement of computer computing power and the development of video processing techniques, video-based event detection has become one of the major functions of today's surveillance systems. Intrusion detection is the most mature technique among all existing event detection techniques, and all intelligent video cameras and video servers offer such a function. “Intrusion” means a moving object moves from an unprotected side to a protected side. Thereby, restricted areas with distinguishable inside and outside or tripwires between unprotected areas and protected areas need to be predefined, and whether a moving object intrudes a system or a region of a user's interest is determined according to aforementioned definitions.
Presently, all the settings of intrusion detection have to be done manually, and the system usually provides a user interface such that a user can draw lines on a video or an image for indicating areas or tripwires. This technique works well in a surveillance system having only a few video cameras. However, it will be too labour-consuming to do all the settings in a large system with hundreds of video cameras. Besides, the settings are done in each video camera individually. Without a systematic methodology of setting and verification, it is almost impossible to ensure that every video camera is correctly set up. It is also difficult for a user to verify if these settings meet the requirements.
Thereby, the development of a multi-level intrusion event detecting system that can automatically analyze the positions of areas and gates in a building, set the security levels of the areas, and generate the corresponding detection areas and tripwires according to the security levels of the areas has become one of the major subjects in the industry.